Lesion-symptom mapping in the study of spoken language understanding

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Lesion-symptom mapping studies aim to make inferences about the functional neuroanatomy of spoken language understanding by investigating relationships between damage to different brain regions and the various speech perception and comprehension deficits that result. Voxel-based lesion-symptom mapping, voxel-based morphometry, and studies focused on specific cortical regions of interest or fibre pathways have all yielded insights regarding the localisation of different components of spoken language processing. Major challenges include the fact that brain damage rarely impacts just a single brain region or just a single processing component, and that neuroplasticity and recovery can complicate the interpretation of lesion-deficit correlations. Future studies involving large patient cohorts derived from multi-centre projects, and multivariate approaches to quantifying patterns of brain damage and patterns of linguistic deficits, will continue to yield new insights into the neural basis of spoken language understanding.

Original languageEnglish (US)
Pages (from-to)1-9
Number of pages9
JournalLanguage, Cognition and Neuroscience
DOIs
StateAccepted/In press - Oct 29 2016
Externally publishedYes

Fingerprint

spoken language
brain damage
deficit
Language
brain
Brain
Neuroanatomy
Speech Perception
Neuronal Plasticity
comprehension
damages
Linguistics
linguistics
interpretation
Lesion
Spoken Language Understanding
Brain Damage

Keywords

  • language comprehension
  • Lesion-symptom mapping
  • magnetic resonance imaging
  • spoken language understanding
  • voxel-based morphometry

ASJC Scopus subject areas

  • Language and Linguistics
  • Experimental and Cognitive Psychology
  • Linguistics and Language
  • Cognitive Neuroscience

Cite this

Lesion-symptom mapping in the study of spoken language understanding. / Wilson, Stephen M.

In: Language, Cognition and Neuroscience, 29.10.2016, p. 1-9.

Research output: Contribution to journalArticle

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